WEBVTT 00:00:00.000 --> 00:00:01.560 When you're working with young individuals is 00:00:01.560 --> 00:00:04.540 make sure you assess maturity because it's going 00:00:04.540 --> 00:00:07.200 to be influential and should be influential in 00:00:07.200 --> 00:00:10.039 terms of your decision making. for maybe talent 00:00:10.039 --> 00:00:12.619 identification if there's much of that going 00:00:12.619 --> 00:00:14.660 on within weightlifting. I know it's generally 00:00:14.660 --> 00:00:17.019 a smaller cohort of athletes, so we don't have 00:00:17.019 --> 00:00:19.280 as much kind of de -selection and recruitment 00:00:19.280 --> 00:00:22.219 going on. But we need to assess maturity to factor 00:00:22.219 --> 00:00:23.879 that in when we're interpreting performance. 00:00:24.440 --> 00:00:26.460 And also it's obviously going to be useful from 00:00:26.460 --> 00:00:30.420 a developmental standpoint to actually be prioritizing 00:00:30.420 --> 00:00:33.500 appropriate things to align natural development 00:00:33.500 --> 00:00:35.899 with an appropriate kind of training stimulus. 00:00:37.960 --> 00:00:41.140 All right, Dr. Stefanie Morris, it's my pleasure 00:00:41.140 --> 00:00:43.640 to have you on Evidence Strong Show for the second 00:00:43.640 --> 00:00:46.200 time. My pleasure having you again and we'll 00:00:46.200 --> 00:00:50.840 be talking maturation and growing up and also 00:00:50.840 --> 00:00:54.100 becoming a weightlifter. So if you could briefly 00:00:54.100 --> 00:00:56.579 introduce yourself, that would be amazing. Thanks 00:00:56.579 --> 00:00:58.740 again for the invite, Alex. Good to talk about 00:00:58.740 --> 00:01:01.159 weightlifting and good to be at the end of the 00:01:01.159 --> 00:01:04.439 PhD journey. So yeah, a bit about me. So recently 00:01:04.439 --> 00:01:07.700 just finished the PhD, which the kind of overarching 00:01:07.700 --> 00:01:10.859 topic was youth weightlifting. And yeah, main 00:01:10.859 --> 00:01:13.200 role is lecturing in strength and conditioning. 00:01:13.480 --> 00:01:15.379 So that's kind of how I got into weightlifting 00:01:15.379 --> 00:01:18.480 is from the using weightlifting as a training 00:01:18.480 --> 00:01:21.079 modality, if you like. And then alongside that, 00:01:21.099 --> 00:01:23.480 obviously get involved in the coaching. So coaching 00:01:23.480 --> 00:01:25.849 weightlifting with British Weightlifting. and 00:01:25.849 --> 00:01:27.870 also coaching strength and conditioning in our 00:01:27.870 --> 00:01:30.450 Youth Athletic Development Centre at Cardiff 00:01:30.450 --> 00:01:33.290 Met. Okay, so we have to start with some kind 00:01:33.290 --> 00:01:37.109 of definition of what relative age and biological 00:01:37.109 --> 00:01:41.150 maturity are. So yeah, relative age kind of refers 00:01:41.150 --> 00:01:44.390 to an individual's calendar age, if you like. 00:01:44.810 --> 00:01:47.250 In relation to the cut -off age within sport, 00:01:47.409 --> 00:01:49.670 so the cut -off age that's normally used to define 00:01:49.670 --> 00:01:53.189 chronological age groups, what we find are what 00:01:53.189 --> 00:01:56.010 we call relative age effects. So often in sport, 00:01:56.049 --> 00:01:59.250 there's a bias towards what we call BQ1 athletes, 00:01:59.430 --> 00:02:02.430 so individuals born in the birth quartile 1 or 00:02:02.430 --> 00:02:04.590 that first quartile relative to the cut -off 00:02:04.590 --> 00:02:07.030 age. And so that's probably most common in a 00:02:07.030 --> 00:02:09.590 lot of sports. But likewise, there are some sports 00:02:09.590 --> 00:02:12.729 where actually there's a bias towards BQ4 athletes 00:02:12.729 --> 00:02:15.479 or those kind of... relatively younger individuals 00:02:15.479 --> 00:02:18.080 compared to that cutoff age. But that's less 00:02:18.080 --> 00:02:20.419 common. And that would be in sports such as like 00:02:20.419 --> 00:02:23.800 gymnastics, diving. We're actually... kind of 00:02:23.800 --> 00:02:26.539 smaller might actually be advantageous I guess 00:02:26.539 --> 00:02:28.740 important to note that sometimes there's some 00:02:28.740 --> 00:02:32.460 confusion between relative age and maturity but 00:02:32.460 --> 00:02:34.560 they need to be recognized as kind of separate 00:02:34.560 --> 00:02:37.300 constructs if you like so just because you have 00:02:37.300 --> 00:02:39.479 a relatively older athlete doesn't mean that 00:02:39.479 --> 00:02:41.960 they'll actually be more mature so biological 00:02:41.960 --> 00:02:45.599 maturity refers to that progress in terms of 00:02:45.599 --> 00:02:48.439 maturation or progressing to a fully mature state 00:02:48.439 --> 00:02:51.840 so different to relative age which relative age 00:02:51.840 --> 00:02:54.620 is kind of that calendar date affected by their 00:02:54.620 --> 00:02:58.360 date of birth whereas maturity refers to kind 00:02:58.360 --> 00:03:01.280 of the state in terms of that biological maturation. 00:03:01.539 --> 00:03:03.599 Please tell us how did you design the study? 00:03:03.759 --> 00:03:06.580 It kind of came about looking at common biases 00:03:06.580 --> 00:03:09.080 in talent identification and like youth sport 00:03:09.080 --> 00:03:11.620 in general and what we know is that in youth 00:03:11.620 --> 00:03:14.960 sport generally individuals are grouped by chronological 00:03:14.960 --> 00:03:18.000 age and that means that we do get these biases 00:03:18.000 --> 00:03:21.159 so we get relative age effects and we get generally 00:03:21.159 --> 00:03:24.500 a bias towards early maturing individuals so 00:03:24.500 --> 00:03:27.379 particularly in boys we know that early maturers 00:03:27.379 --> 00:03:30.939 generally are kind of stronger heavier potentially 00:03:30.939 --> 00:03:33.319 more confident than their peers and that leads 00:03:33.319 --> 00:03:36.620 to athletic advantages and what we knew was that 00:03:36.620 --> 00:03:38.539 these biases were common in a lot of other sports 00:03:38.539 --> 00:03:41.159 so there's been a lot done in football for example 00:03:41.680 --> 00:03:44.199 age effects and maturity biases but um there 00:03:44.199 --> 00:03:46.060 really hadn't been much done in weightlifting 00:03:46.060 --> 00:03:48.020 there were a couple of studies that looked at 00:03:48.020 --> 00:03:50.460 relative age effects but actually maturity is 00:03:50.460 --> 00:03:52.580 arguably a little bit more important and definitely 00:03:52.580 --> 00:03:55.240 more influential as well so we just wanted to 00:03:55.240 --> 00:03:57.699 fill a bit of a gap there and explore maturity 00:03:57.699 --> 00:04:01.120 and also look at the influence as well so we 00:04:01.120 --> 00:04:04.219 know that as individuals mature we get big changes 00:04:04.219 --> 00:04:06.719 in strength and power and whatnot actually there 00:04:06.719 --> 00:04:08.939 wasn't any research that looked at the relationship 00:04:08.939 --> 00:04:11.330 between maturity and weight lifting performance. 00:04:11.729 --> 00:04:14.310 All right. So you decided, right, we have to 00:04:14.310 --> 00:04:17.490 have a look at young weightlifters. So who did 00:04:17.490 --> 00:04:21.589 you invite to the study? Yeah. So it was, I went 00:04:21.589 --> 00:04:25.129 along to the English age groups. And that was 00:04:25.129 --> 00:04:27.170 kind of through links with British weightlifting. 00:04:27.269 --> 00:04:29.670 So they've been really receptive to all of it. 00:04:29.730 --> 00:04:31.930 And it was kind of like, OK, can I come along 00:04:31.930 --> 00:04:34.889 to one of your events? And we chose the English 00:04:34.889 --> 00:04:38.370 age groups or kind of championships because the 00:04:38.370 --> 00:04:41.370 idea was we wanted that high level of performance. 00:04:41.629 --> 00:04:44.370 And so we wanted to explore, actually, was there 00:04:44.370 --> 00:04:47.769 a bias? And were we almost like selecting or 00:04:47.769 --> 00:04:50.230 cutting off some of those individuals that weren't 00:04:50.230 --> 00:04:52.490 then reaching those kind of higher participation 00:04:52.490 --> 00:04:56.089 levels? So yeah, I went along to the English 00:04:56.089 --> 00:04:59.449 age group championships and we managed to recruit, 00:04:59.550 --> 00:05:02.870 it was 49 young weightlifters. And that was across 00:05:02.870 --> 00:05:06.129 all of the age group categories competing. So 00:05:06.129 --> 00:05:10.170 under 10s, under 12s, under 15s and under 17s. 00:05:10.170 --> 00:05:12.769 And we had a spread across those age groups. 00:05:12.949 --> 00:05:15.829 And also it was almost a 50 -50 split between 00:05:15.829 --> 00:05:18.470 boys and girls within that cohort as well. Awesome. 00:05:18.569 --> 00:05:20.990 What did you measure? So what we did was, so 00:05:20.990 --> 00:05:23.399 when we look at assessing. biological maturity 00:05:23.399 --> 00:05:26.759 what we often or what we have are kind of three 00:05:26.759 --> 00:05:29.439 systems that we can measure maturity across if 00:05:29.439 --> 00:05:32.540 you like so we have sexual maturity skeletal 00:05:32.540 --> 00:05:37.120 maturity and somatic maturity and often sexual 00:05:37.120 --> 00:05:39.720 maturity isn't used as much in practice so to 00:05:39.720 --> 00:05:42.579 measure sexual maturity a common method is using 00:05:42.579 --> 00:05:45.079 tanner stages where you kind of use criteria 00:05:45.079 --> 00:05:48.040 and look at kind of like pubic hair development 00:05:48.040 --> 00:05:51.560 and kind of categorize them obviously quite invasive 00:05:51.980 --> 00:05:53.939 practitioner to do it and then there are self 00:05:53.939 --> 00:05:56.259 -reported measures but they're less reliable 00:05:56.259 --> 00:05:59.689 so commonly Sexual maturity isn't used that often. 00:05:59.829 --> 00:06:03.430 We've then got skeletal maturity. And often that's 00:06:03.430 --> 00:06:06.290 seen as like the gold standard way of assessing 00:06:06.290 --> 00:06:09.430 biological maturity. But that involves x -rays. 00:06:09.569 --> 00:06:11.970 And so obviously quite costly, also not that 00:06:11.970 --> 00:06:14.550 accessible. But what they've recently introduced 00:06:14.550 --> 00:06:18.769 is ultrasound equipment. And we used a kind of 00:06:18.769 --> 00:06:22.529 equipment called sonic bone, which uses a similar 00:06:22.529 --> 00:06:26.930 method to the x -rays and actually uses the Tanner. 00:06:27.149 --> 00:06:30.050 white house two method to categorize and that 00:06:30.050 --> 00:06:33.230 gives us an estimation of skeletal maturity using 00:06:33.230 --> 00:06:35.949 ultrasound rather than the x -rays so we don't 00:06:35.949 --> 00:06:38.430 have the kind of exposure and that we'd get with 00:06:38.430 --> 00:06:41.709 the x -rays and also it's a lot more accessible 00:06:41.709 --> 00:06:43.930 and so that was actually the method that we use 00:06:43.930 --> 00:06:47.149 so um i took along the sonic bone so it's a piece 00:06:47.149 --> 00:06:50.389 of equipment not not big at all and took measurements 00:06:50.389 --> 00:06:52.970 so what we do with the that equipment is we take 00:06:52.970 --> 00:06:56.050 three measurements on different sites on the 00:06:56.050 --> 00:06:58.790 left hand and wrist area. And what it does is 00:06:58.790 --> 00:07:01.350 it uses those measurements. So it kind of takes 00:07:01.350 --> 00:07:04.189 like the speed of sound and attenuation and then 00:07:04.189 --> 00:07:06.949 gives us an estimated skeletal age based off 00:07:06.949 --> 00:07:09.410 that. That's pretty cool. Yeah, yeah. So yeah, 00:07:09.470 --> 00:07:12.889 it's kind of fairly new and we've only just started 00:07:12.889 --> 00:07:14.990 using that piece of equipment over the last couple 00:07:14.990 --> 00:07:17.189 of years. And I think it's important to note 00:07:17.189 --> 00:07:19.790 that like that would probably be seen as like 00:07:19.790 --> 00:07:23.250 a more rigorous approach in research to estimate. 00:07:23.740 --> 00:07:27.019 kind of maturity but likewise and one of the 00:07:27.019 --> 00:07:29.459 review papers that we've actually published since 00:07:29.459 --> 00:07:32.100 kind of gives guidance on that the other method 00:07:32.100 --> 00:07:35.120 that i discussed of using somatic measurements 00:07:35.120 --> 00:07:38.420 to determine kind of somatic maturity so that's 00:07:38.420 --> 00:07:41.279 obviously easily accessible to coaches by just 00:07:41.279 --> 00:07:43.379 taking height and weight and we get you know 00:07:43.379 --> 00:07:45.939 it's reliable enough not as kind of accurate 00:07:45.939 --> 00:07:48.879 as the sonic bone but we kind of it's a lot more 00:07:48.879 --> 00:07:51.959 accessible in practice yeah so yeah we also took 00:07:51.959 --> 00:07:54.680 height and weight which we input that information 00:07:54.680 --> 00:07:57.500 to help with the equations as well and then the 00:07:57.500 --> 00:08:00.839 individuals reported their competition performance 00:08:00.839 --> 00:08:04.319 and so we reported obviously their maximum across. 00:08:04.860 --> 00:08:07.519 clean and jerk and snatch their total and then 00:08:07.519 --> 00:08:10.060 we also then converted those into relative measures 00:08:10.060 --> 00:08:12.600 as well just to explore the influence of maturity 00:08:12.600 --> 00:08:15.519 across absolute but also relative measures of 00:08:15.519 --> 00:08:18.060 weight lifting performance how do you get from 00:08:18.060 --> 00:08:22.560 height and weight to the maturity status or or 00:08:22.560 --> 00:08:26.360 growth status of a person yeah yeah so yeah the 00:08:26.360 --> 00:08:29.620 sonic bone kind of uses those as part of the 00:08:29.620 --> 00:08:32.580 equation but what what we kind of typically recommend 00:08:32.580 --> 00:08:36.179 and how we use somatic measures to get maturity 00:08:36.179 --> 00:08:40.399 status is um using the commonly two equations 00:08:40.399 --> 00:08:43.740 that are most commonly used and we recommend 00:08:43.740 --> 00:08:47.159 the camison roach method which takes standing 00:08:47.159 --> 00:08:50.580 height and also parental height as well so we 00:08:50.580 --> 00:08:53.590 didn't actually use that in this study but generally 00:08:53.590 --> 00:08:56.970 there's better reliability. And it uses equations 00:08:56.970 --> 00:08:59.990 to look at what's the individual's predicted 00:08:59.990 --> 00:09:02.250 adult height. And then from the measurement of 00:09:02.250 --> 00:09:04.210 their standard height and weight, we can add 00:09:04.210 --> 00:09:06.129 in seated height as well, but it doesn't make 00:09:06.129 --> 00:09:08.629 a massive difference. And then from that, we 00:09:08.629 --> 00:09:10.789 can determine what's their current percentage 00:09:10.789 --> 00:09:13.629 of predicted adult height. And then from that, 00:09:13.690 --> 00:09:17.110 we can align those percentages to a kind of maturity 00:09:17.110 --> 00:09:20.730 status. Do you want to say what kind of analysis 00:09:20.730 --> 00:09:23.809 did you do? at the kind of whether there was 00:09:23.809 --> 00:09:26.970 a bias towards maturity or whether there were 00:09:26.970 --> 00:09:30.210 relative age effects um we ran um chi -square 00:09:30.210 --> 00:09:32.610 analysis and that basically shows us if there 00:09:32.610 --> 00:09:36.370 is a difference to um what we'd expect so looked 00:09:36.370 --> 00:09:39.190 at what's kind of normal distribution so how 00:09:39.190 --> 00:09:41.850 many would we normally expect in birth quartile 00:09:41.850 --> 00:09:44.629 one birth quartile two three four how many would 00:09:44.629 --> 00:09:47.870 we normally expect as early on time or late matures 00:09:47.870 --> 00:09:51.149 um and then the chi -square analysis looks at 00:09:51.149 --> 00:09:53.120 what we'd expect compared to what we actually 00:09:53.120 --> 00:09:56.139 found and then the second analysis was then looking 00:09:56.139 --> 00:09:59.399 at some regression so we actually conducted rather 00:09:59.399 --> 00:10:02.259 than linear regression we did power regression 00:10:02.259 --> 00:10:05.580 so quite often we do linear regression when we're 00:10:05.580 --> 00:10:07.720 looking at predictions but actually we know that 00:10:07.720 --> 00:10:10.840 maturity isn't a linear process so what we found 00:10:10.840 --> 00:10:13.700 was that the power regression analysis was kind 00:10:13.700 --> 00:10:16.799 of a better fit and provided a better relationship 00:10:16.799 --> 00:10:19.419 between those variables. So we did a power regression 00:10:19.419 --> 00:10:21.580 analysis looking at weightlifting performance 00:10:21.580 --> 00:10:25.009 and then skeletal age. Awesome. Are we ready 00:10:25.009 --> 00:10:29.009 for the results? Yeah. Go there. So yeah, what 00:10:29.009 --> 00:10:31.850 we found in terms of birth quartile, there were 00:10:31.850 --> 00:10:34.409 no, it wasn't different to what we'd expect. 00:10:34.610 --> 00:10:37.210 So in this cohort, there were no relative age 00:10:37.210 --> 00:10:39.909 effects. And that was across all of the sample, 00:10:39.909 --> 00:10:42.889 but also within the individual age groups. And 00:10:42.889 --> 00:10:45.490 then probably the most interesting was the maturity 00:10:45.490 --> 00:10:48.870 bias. So what we found across the group collectively 00:10:48.870 --> 00:10:52.169 in both boys and girls individually, there was 00:10:52.169 --> 00:10:54.429 an over -representation of... early maturers 00:10:54.429 --> 00:10:57.690 and also more than what we'd expect of on -time 00:10:57.690 --> 00:11:00.509 maturers. And it was particularly the under 15 00:11:00.509 --> 00:11:03.269 age group when we looked at those across the 00:11:03.269 --> 00:11:05.210 individual age groups. It was the under 15 age 00:11:05.210 --> 00:11:07.990 group that saw that over -representation of early 00:11:07.990 --> 00:11:10.389 maturers. And then the kind of second analysis, 00:11:10.470 --> 00:11:13.139 looking at the relationships. What we found was 00:11:13.139 --> 00:11:16.159 that really strong relationships between skeletal 00:11:16.159 --> 00:11:17.980 age and weightlifting performance kind of as 00:11:17.980 --> 00:11:22.080 we'd expect. So it was in the boys, skeletal 00:11:22.080 --> 00:11:26.539 age was able to explain it was 73 % of variance 00:11:26.539 --> 00:11:29.679 and then in the girls, 75 % of variance. And 00:11:29.679 --> 00:11:31.559 then we actually looked at whether there was 00:11:31.559 --> 00:11:33.740 a difference between the relationship between 00:11:33.740 --> 00:11:36.039 weightlifting and skeletal age in boys and girls. 00:11:36.200 --> 00:11:38.220 And there was a difference and that difference 00:11:38.220 --> 00:11:41.799 tended to emerge around that like. 12 to 13 years 00:11:41.799 --> 00:11:45.039 so again just kind of add into the notion of 00:11:45.039 --> 00:11:47.909 the importance of assessing maturity And then 00:11:47.909 --> 00:11:50.710 also differences in males and females, and they 00:11:50.710 --> 00:11:52.970 are typically going to emerge around that adolescent 00:11:52.970 --> 00:11:55.929 growth spurt, kind of as we'd expect. What coaches 00:11:55.929 --> 00:11:58.570 should take away from this study? I guess the 00:11:58.570 --> 00:12:01.210 importance initially is when you're working with 00:12:01.210 --> 00:12:03.850 young individuals is make sure you assess maturity 00:12:03.850 --> 00:12:06.789 because it's going to be influential and should 00:12:06.789 --> 00:12:08.750 be influential in terms of your decision making 00:12:08.750 --> 00:12:12.549 for maybe talent identification. If there's much 00:12:12.549 --> 00:12:14.529 of that going on within weightlifting, I know 00:12:14.529 --> 00:12:16.509 it's generally a smaller cohort of athletes. 00:12:16.909 --> 00:12:19.429 we don't have as much kind of de -selection and 00:12:19.429 --> 00:12:22.149 recruitment going on but we need to assess maturity 00:12:22.149 --> 00:12:24.389 to factor that in when we were interpreting performance 00:12:24.389 --> 00:12:26.929 and also it's obviously going to be useful from 00:12:26.929 --> 00:12:30.889 a developmental standpoint to actually be prioritizing 00:12:30.889 --> 00:12:33.990 appropriate things to align natural development 00:12:33.990 --> 00:12:36.509 with an appropriate kind of training stimulus. 00:12:36.830 --> 00:12:39.450 Would you have any examples for that? Yeah so 00:12:39.450 --> 00:12:43.230 a kind of Key example might be post peak height 00:12:43.230 --> 00:12:45.929 velocity, particularly in boys, we might see 00:12:45.929 --> 00:12:48.389 increases in circulating hormones, which mean 00:12:48.389 --> 00:12:51.750 that we get large increases in strength and the 00:12:51.750 --> 00:12:54.470 ability to kind of increase muscle mass. So adding 00:12:54.470 --> 00:12:56.809 additional load at this point in the weightlifting 00:12:56.809 --> 00:12:59.029 movements, as long as we've got sound technical 00:12:59.029 --> 00:13:01.649 proficiency, we'll take advantage and we'll almost 00:13:01.649 --> 00:13:04.389 see kind of like a synergistic adaptation at 00:13:04.389 --> 00:13:08.350 this point, potentially around that growth spurt. 00:13:08.450 --> 00:13:11.639 So circa peak height velocity. and often we might 00:13:11.899 --> 00:13:14.120 see this period of like adolescent awkwardness 00:13:14.120 --> 00:13:16.899 so we might see like breakdowns in movement snatch 00:13:16.899 --> 00:13:19.779 in particular for example um that's maybe deemed 00:13:19.779 --> 00:13:21.799 a little bit more technical might become a little 00:13:21.799 --> 00:13:24.120 bit clunky it might perfect lift one day next 00:13:24.120 --> 00:13:26.740 day the athletes all over the place so at that 00:13:26.740 --> 00:13:29.500 stage we might want to kind of pull back on some 00:13:29.500 --> 00:13:32.600 of the technical elements and maybe use the derivatives 00:13:32.600 --> 00:13:35.100 or parts of the movement a little bit more commonly 00:13:35.100 --> 00:13:37.200 than the full movements and we might want to 00:13:37.200 --> 00:13:40.379 supplement normal training with maybe some mobility 00:13:40.379 --> 00:13:43.340 to cater for reductions in mobility that we might 00:13:43.340 --> 00:13:45.440 see at that phase or potentially an emphasis 00:13:45.440 --> 00:13:47.720 on like full range of movement in some of those 00:13:47.720 --> 00:13:49.799 strength exercises and then the other one would 00:13:49.799 --> 00:13:52.539 be typically pre -peak height velocity so before 00:13:52.539 --> 00:13:55.860 that growth spurt generally we see a increase 00:13:55.860 --> 00:13:59.240 in neuroplasticity so individuals can potentially 00:13:59.240 --> 00:14:01.580 pick up movements and learn movement patterns 00:14:01.580 --> 00:14:04.379 quite easily and so introducing weightlifting 00:14:04.379 --> 00:14:06.480 ideally at that stage to learn the movements 00:14:06.480 --> 00:14:09.460 and to then kind of progress and add load once 00:14:09.460 --> 00:14:11.590 they've got that technical proficiency and kind 00:14:11.590 --> 00:14:13.690 of potentially adding in some other neuromuscular 00:14:13.690 --> 00:14:16.669 training at that stage to take advantage of what's 00:14:16.669 --> 00:14:18.690 what's naturally occurring so plyometrics at 00:14:18.690 --> 00:14:21.350 that stage a bit more of like a combined training 00:14:21.350 --> 00:14:23.769 approach and you think coaches should be aware 00:14:23.769 --> 00:14:27.330 in terms of differences between how to train 00:14:27.330 --> 00:14:30.669 boys versus girls yeah so i guess one of the 00:14:30.669 --> 00:14:34.779 things that we might want to consider is Girls, 00:14:34.779 --> 00:14:37.500 particularly at that post peak height velocity 00:14:37.500 --> 00:14:40.820 stage, because of their seeing natural increases 00:14:40.820 --> 00:14:43.919 in fat mass, more so compared to boys, their 00:14:43.919 --> 00:14:46.299 relative strength might actually kind of stay 00:14:46.299 --> 00:14:49.759 the same. So being mindful of that. And at that 00:14:49.759 --> 00:14:52.379 stage, we're going to try and avoid male and 00:14:52.379 --> 00:14:54.740 female comparisons as much as possible, but also 00:14:54.740 --> 00:14:58.000 avoid in peer to peer comparisons, particularly 00:14:58.000 --> 00:15:00.559 in young females as well. So some of the research 00:15:00.559 --> 00:15:03.720 from like. psychological perspective shows that 00:15:03.720 --> 00:15:07.039 post peak heart velocity young girls are particularly 00:15:07.039 --> 00:15:09.840 like critical and comparing themselves to peers 00:15:09.840 --> 00:15:12.940 so from a confidence perspective an emphasis 00:15:12.940 --> 00:15:16.340 on like individual growth and kind of got individual 00:15:16.340 --> 00:15:19.080 group like goal setting and progress might be 00:15:19.080 --> 00:15:21.000 particularly important in the girls but also 00:15:21.000 --> 00:15:23.720 in the boys arguably as well avoiding that kind 00:15:23.720 --> 00:15:26.480 of peer comparison yeah and I guess probably 00:15:26.480 --> 00:15:29.519 so that focuses on almost like maturity status 00:15:29.519 --> 00:15:32.399 but also considering Maturity timing as well 00:15:32.399 --> 00:15:34.720 would be important. So whether your individual 00:15:34.720 --> 00:15:37.679 is an early on time or late maturer, because 00:15:37.679 --> 00:15:40.440 that then might have implications from a training 00:15:40.440 --> 00:15:42.840 perspective as well. So again, kind of sticking 00:15:42.840 --> 00:15:45.970 on the psychology, what we know is that. early 00:15:45.970 --> 00:15:48.929 maturing females might see lower levels of self 00:15:48.929 --> 00:15:51.250 -confidence compared to the males that actually 00:15:51.250 --> 00:15:53.649 might see higher levels of self -confidence and 00:15:53.649 --> 00:15:56.389 so being mindful of that and again avoiding peer 00:15:56.389 --> 00:16:00.129 comparisons kind of throughout that growth spurt 00:16:00.129 --> 00:16:02.870 and adolescent phase and obviously weightlifting 00:16:02.870 --> 00:16:05.110 is a sport where the comparisons are really easy 00:16:05.110 --> 00:16:07.870 we've literally got weight lifted but I think 00:16:07.870 --> 00:16:10.210 one of the guidance that we pulled together was 00:16:10.649 --> 00:16:14.070 adding in maybe like handicapped scoring systems 00:16:14.070 --> 00:16:16.789 for in -house competitions where athletes are 00:16:16.789 --> 00:16:19.210 compared to their personal best rather than always 00:16:19.210 --> 00:16:21.710 kind of comparing to others within those kind 00:16:21.710 --> 00:16:24.490 of categories or genders. Okay, we have some 00:16:24.490 --> 00:16:29.690 options. Yeah. And to not discourage or write 00:16:29.690 --> 00:16:32.190 off the athletes who are maturing later. That's 00:16:32.190 --> 00:16:34.649 important. Yeah, and I guess we kind of touched 00:16:34.649 --> 00:16:37.629 on it earlier about how the under 15 age category 00:16:37.629 --> 00:16:40.470 doesn't have that technical element. So it's 00:16:40.470 --> 00:16:42.789 whether, particularly in in -house competitions, 00:16:42.909 --> 00:16:45.470 we could bring that technical assessment and 00:16:45.470 --> 00:16:47.509 the influence that has on their overall score 00:16:47.509 --> 00:16:50.450 back in a little bit more. Obviously, generally, 00:16:50.669 --> 00:16:53.149 athletes with better technical competency will 00:16:53.149 --> 00:16:55.250 lift more, but it doesn't always work like that. 00:16:55.389 --> 00:16:57.750 And you may see the athletes that have poor technical 00:16:57.750 --> 00:17:00.309 competency, but because they have kind of better 00:17:00.309 --> 00:17:02.129 strength or power, they can get away with it 00:17:02.129 --> 00:17:04.549 a little bit more. So maybe adding in some technical 00:17:04.549 --> 00:17:07.150 scoring as well might complement that. Measuring 00:17:07.150 --> 00:17:10.019 maturity, adjusting competition. So they are 00:17:10.019 --> 00:17:12.740 a little bit fair through keeping this technical 00:17:12.740 --> 00:17:16.619 element up to 15 years of age, where these differences 00:17:16.619 --> 00:17:20.240 are biasing the outcome, potentially, as they 00:17:20.240 --> 00:17:24.000 did in the study. And using this information 00:17:24.000 --> 00:17:27.859 to program and to guide and develop athletes 00:17:27.859 --> 00:17:31.519 according to their actual biological maturation 00:17:31.519 --> 00:17:35.200 stage, not necessary to the date they were born. 00:17:35.359 --> 00:17:37.700 Two questions to finish. The first one is, what 00:17:37.700 --> 00:17:39.980 is your favorite... I'm going to go really controversial 00:17:39.980 --> 00:17:43.140 as a, in theory, weightlifter, but at the moment 00:17:43.140 --> 00:17:46.460 it's got to be a split squat. What? What? Sorry. 00:17:46.619 --> 00:17:50.519 I just think, well, I... hurt my ankle I spray 00:17:50.519 --> 00:17:53.099 my ankle before Christmas and squatting just 00:17:53.099 --> 00:17:55.660 it's not enjoyable at the moment doesn't look 00:17:55.660 --> 00:17:58.279 as good and you can't beat a split squat just 00:17:58.279 --> 00:18:01.299 to keep that strength development up and not 00:18:01.299 --> 00:18:04.319 compromise on my form with my bad ankle got it 00:18:04.319 --> 00:18:06.680 got it I respect that all right where people 00:18:06.680 --> 00:18:09.660 can find you if they want to follow your research 00:18:09.660 --> 00:18:12.299 ask a question or just see what you're up to 00:18:12.299 --> 00:18:14.859 where should they go I'm rubbish on social media 00:18:14.859 --> 00:18:17.839 and I apologize now I'm always really good on 00:18:17.839 --> 00:18:20.319 email. I'm one of those losers. So any questions, 00:18:20.319 --> 00:18:23.700 by all means, I welcome an email. But I do have 00:18:23.700 --> 00:18:26.660 social media, so I can be found on Twitter. I'm 00:18:26.660 --> 00:18:28.619 also pretty good on ResearchGate as well. If 00:18:28.619 --> 00:18:30.740 anybody wants any of the research kind of sharing 00:18:30.740 --> 00:18:33.700 or whatnot, probably best to drop a message in 00:18:33.700 --> 00:18:38.420 my inbox on ResearchGate. X is at StephMorris979. 00:18:38.579 --> 00:18:40.140 But yeah, maybe if people message me on there, 00:18:40.180 --> 00:18:41.940 I might become a little bit better. Excellent. 00:18:42.240 --> 00:18:44.099 Incentive. All right, Sveta. Thank you so, so 00:18:44.099 --> 00:18:46.519 much. Pleasure to meet you again and all the 00:18:46.519 --> 00:18:47.779 best. Yeah. Thank you, Alex.